Audio transmission processing method and device, electronic equipment and readable storage medium

Abstract

The invention provides an audio transmission processing method and device, electronic equipment and a readable storage medium, and belongs to the technical field of audio processing, and the method comprises the steps: carrying out the preprocessing of a first audio signal, and obtaining a second audio signal; determining an audio scene corresponding to the second audio signal based on the matching degree of the second audio signal and the reference audio signal; and selecting a target channel based on the audio scene to transmit the second audio signal. According to the audio transmission processing method and device, the electronic equipment and the readable storage medium provided by the invention, the problem that the transmission quality of the audio signal cannot be guaranteed can be solved.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of audio processing, and more specifically, to an audio transmission processing method, device, electronic device, and readable storage medium. Background Art

[0002] With the popularization of smart devices and the rapid development of audio technology, the accuracy and efficiency of audio transmission have become key factors affecting user experience. However, the audio transmission methods in the prior art often lack intelligent recognition and adaptation of the environment in which the audio signal is located, resulting in the inability to ensure the transmission quality of the audio signal in different audio scenarios. Summary of the invention

[0003] The purpose of the present disclosure is to provide an audio transmission processing method, device, electronic device, and readable storage medium to solve the problem that the transmission quality of audio signals cannot be guaranteed.

[0004] According to a first aspect of the present disclosure, there is provided an audio transmission processing method, including: Preprocessing the first audio signal to obtain a second audio signal; determining an audio scene corresponding to the second audio signal based on a matching degree between the second audio signal and a reference audio signal; A target channel is selected based on the audio scene to transmit the second audio signal.

[0005] According to a second aspect of the embodiments of the present disclosure, there is provided an audio transmission processing device, including: A preprocessing module, used for preprocessing the first audio signal to obtain a second audio signal; a scene determination module, configured to determine an audio scene corresponding to the second audio signal based on a matching degree between the second audio signal and a reference audio signal; A signal transmission module is used to select a target channel based on the audio scene to transmit the second audio signal.

[0006] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the above-mentioned audio transmission processing method when executing the computer program.

[0007] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned audio transmission processing method are implemented.

[0008] The beneficial effects of the audio transmission processing method, device, electronic device, and readable storage medium provided by the embodiments of the present disclosure are: the embodiments of the present disclosure use audio scene recognition technology to accurately match audio signals with preset reference audio signals, thereby intelligently identifying the specific environment or application scenario in which the audio signal is located. The embodiments of the present disclosure can also flexibly select the target channel that best suits the current audio scene for signal transmission, ensuring the efficiency, stability, and adaptability of audio signal transmission. It not only improves the reliability of audio transmission and user experience, but also provides strong technical support for audio communications in different application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 A flowchart of an audio transmission processing method provided by an embodiment of the present disclosure; Figure 2 A structural block diagram of an audio transmission processing device provided by an embodiment of the present disclosure; Figure 3 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0011] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0012] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0013] Please refer to Figure 1 , Figure 1 A flowchart of an audio transmission processing method provided by an embodiment of the present disclosure is provided, and the method includes: S101: pre-process a first audio signal to obtain a second audio signal.

[0014] In this embodiment, the first audio signal is an unprocessed original audio signal; and the second audio signal is a pre-processed audio signal.

[0015] In this embodiment, the first audio signal may be subjected to filtering, noise reduction, gain adjustment, format conversion and other processing to obtain the second audio signal.

[0016] Filtering can remove noise in a specific frequency range through low-pass filtering, high-pass filtering, band-pass filtering, etc. For example, it can remove low-frequency environmental noise or high-frequency electromagnetic interference. Noise reduction can use adaptive filtering, spectral subtraction, etc. to reduce the impact of environmental noise on audio signals and improve the signal-to-noise ratio of the signal. Gain adjustment can automatically adjust the gain according to the strength of the audio signal to keep the volume of the audio signal within an appropriate range and avoid excessive or low volume. Format conversion can convert audio signals with different sampling rates to a unified sampling rate for subsequent analysis and processing.

[0017] Exemplarily, in an intelligent voice assistant device, the intelligent voice assistant needs to accurately receive and process the user's voice command, and communicate with the server to obtain corresponding feedback information. The user's voice command is collected through the built-in microphone of the device to obtain a first audio signal. At this time, the first audio signal is an unprocessed original audio signal, which may contain adverse factors such as environmental noise and electromagnetic interference.

[0018] The first audio signal is low-pass filtered to remove high-frequency electromagnetic interference. For example, the cutoff frequency is set to 10kHz, and the signal components above the frequency are filtered out. At the same time, high-pass filtering is performed to remove low-frequency environmental noise, such as noise generated by air conditioners, fans, etc. The cutoff frequency is set to 100Hz, and the signal components below the frequency are filtered out. The audio signal is denoised using an adaptive filtering algorithm. By analyzing the statistical characteristics of the audio signal, the filter parameters are adaptively adjusted to minimize the impact of environmental noise on the audio signal. For example, according to the power spectral density estimate of the noise, the filter coefficients are adjusted to minimize the error between the signal output by the filter and the original audio signal. The automatic gain control algorithm is used to monitor the amplitude of the audio signal in real time and adjust it according to a preset target amplitude range. For example, if the amplitude of the audio signal is lower than the target range, the gain is increased; if the amplitude is higher than the target range, the gain is reduced. The sampling rate supported by the device is 16kHz, and the first audio signal collected has a different sampling rate. The sampling rate of the audio signal is converted to 16kHz using a sampling rate conversion algorithm, and the second audio signal is obtained after the above processing.

[0019] In this embodiment, by preprocessing the first audio signal, a second audio signal with higher quality is obtained, thereby improving the accuracy of speech recognition and the response speed of the intelligent voice assistant.

[0020] S102: Determine an audio scene corresponding to the second audio signal based on a matching degree between the second audio signal and the reference audio signal.

[0021] In this embodiment, the reference audio signal is a predefined audio signal representing different audio scenes; the matching degree is an indicator used to measure the similarity between the second audio signal and the reference audio signal. The audio scene is a specific environment or application scene in which the audio signal is located.

[0022] In one embodiment of the present disclosure, constructing an audio scene recognition model includes: Processing the multiple audio scene information to obtain multiple first audio scene information; The audio scene features of the plurality of first audio scene information are trained based on the target model to obtain a mapping relationship between the audio scene features and the corresponding audio scenes.

[0023] In this embodiment, an audio data set containing multiple audio scenes (such as concerts, outdoor environments, and inside vehicles, etc.) is collected. A machine learning or deep learning model is selected for training (such as a support vector machine, a convolutional neural network, a recurrent neural network, etc.), which can learn the mapping relationship between audio signal features and their corresponding scenes. The audio scene features are used as the features of the reference audio signal.

[0024] In this embodiment, feature extraction is performed on the second audio signal and the reference audio signal to obtain first feature information; and the similarity between the first feature information and the audio scene feature is calculated.

[0025] In this embodiment, feature extraction is performed on the second audio signal and the reference audio signal. These features may include spectral features, time domain features, etc., which may reflect different characteristics of the audio signal. For example, spectral features may reveal the frequency distribution of the audio signal, and time domain features may reflect the law of change of the audio signal over time. The similarity between the features of the second audio signal and the features of each reference audio signal is calculated. Commonly used similarity calculation methods include Euclidean distance, cosine similarity, etc. The higher the similarity, the more similar the second audio signal is to the reference audio signal. Based on the result of the similarity calculation, the audio scene corresponding to the second audio signal is determined. The audio scene represented by the reference audio signal with the highest similarity may be selected as the scene of the second audio signal.

[0026] S103: Select a target channel to transmit the second audio signal based on the audio scene.

[0027] In this embodiment, the target channel refers to a specific channel selected from available communication channels according to the requirements of the audio scene for transmitting the second audio signal. The communication channel may include various wired and wireless communication methods, such as Wi-Fi, Bluetooth, mobile network (4G, 5G), etc.

[0028] In this embodiment, parameter information of a target channel is acquired based on an audio scene; a target channel is selected based on the audio scene and the parameter information; and the second audio signal is transmitted based on the target channel.

[0029] In this embodiment, after the audio scene is determined, the list of available channels (target channels) is queried. Parameters of each available channel are measured, such as measuring the delay and packet loss rate by sending a test data packet, and estimating the bandwidth and signal-to-noise ratio by analyzing the frequency response of the channel. According to the requirements of the audio scene and the parameter information of the channel, the channels are evaluated and sorted by selecting an algorithm (such as a weighted average method, a priority sorting method, etc.). The highest ranked channel is selected as the target channel, and the second audio signal is transmitted through the channel.

[0030] For example, for voice call scenarios, this embodiment can give priority to channels with low latency and stable connections, such as 4G networks or dedicated voice communication channels; for music playback scenarios, this embodiment can select a Wi-Fi channel with a larger bandwidth to ensure smooth audio transmission and high sound quality.

[0031] For example, suppose we have a smart music playing device that needs to provide users with high-quality music playing experience in different environments.

[0032] The device collects audio signals through the built-in microphone to obtain a first audio signal. At this time, the first audio signal may contain environmental noise, such as surrounding human voices and the sound of electrical appliances. Perform low-pass filtering and set the cutoff frequency to 15kHz to filter out high-frequency electromagnetic interference. Perform high-pass filtering and set the cutoff frequency to 80Hz to remove low-frequency environmental noise. Adaptive filtering algorithm is used for noise reduction processing. The filter coefficient is adjusted according to the power spectral density estimate of the noise to minimize the error between the signal output by the filter and the original audio signal. Since the sampling rate supported by the device is 44.1kHz, and the sampling rate of the collected first audio signal is 48kHz, the sampling rate conversion is performed to convert the audio signal to 44.1kHz to obtain the second audio signal.

[0033] Extract the spectral features and time domain features of the second audio signal and the reference audio signal. Use the cosine similarity calculation method to calculate the similarity between the features of the second audio signal and the features of each reference audio signal, and determine the audio scene corresponding to the second audio signal based on the similarity calculation result. For example, if the similarity with the reference audio signal of the indoor quiet environment is the highest, then determine that the current audio scene is an indoor quiet environment.

[0034] After determining that the audio scene is a quiet indoor environment, query the list of available channels, including Wi-Fi, Bluetooth, and 4G networks. Perform parameter measurements on each available channel, measure the delay and packet loss rate by sending test data packets, and analyze the frequency response of the channel to estimate the bandwidth and signal-to-noise ratio. According to the audio scene and parameter information, the weighted average method is used to evaluate and sort the channels. For the music playback scenario, bandwidth and stability are more important and are given higher weights. Assuming that the Wi-Fi channel ranks highest in the evaluation, select the Wi-Fi channel as the target channel. Transmit the second audio signal through the Wi-Fi channel to provide users with a smooth music playback experience.

[0035] It can be concluded from the above that this embodiment uses audio scene recognition technology to accurately match audio signals with preset reference audio signals, thereby intelligently identifying the specific environment or application scenario in which the audio signal is located. This embodiment can also flexibly select the target channel that best suits the current audio scene for signal transmission, ensuring the efficiency, stability and adaptability of audio signal transmission. It not only improves the reliability of audio transmission and user experience, but also provides strong technical support for audio communications in different application scenarios.

[0036] In an embodiment of the present disclosure, before determining the audio scene corresponding to the second audio signal based on the matching degree between the second audio signal and the reference audio signal, the method further includes: Calculating the similarity between the first feature information and the second feature information; Determining a matching degree between the second audio signal and the reference audio signal based on a similarity between the first feature information and the second feature information; The first feature information is feature information of the second audio signal, and the second feature information is feature information of the reference audio signal.

[0037] In this embodiment, feature extraction is performed on the second audio signal to obtain first feature information; feature extraction is performed on the reference audio signal to obtain second feature information; the first feature information and the second feature information are input into a similarity calculation model to calculate similarity.

[0038] In this embodiment, the first feature information and the second feature information may be spectral features, time domain features, etc. Different features may reflect different characteristics of the audio signal. The similarity calculation model may be Euclidean distance, cosine similarity, etc. Different similarity calculation models are suitable for different types of features and application scenarios. Euclidean distance is applicable to numerical features and calculates the geometric distance between two feature vectors in multidimensional space. The smaller the distance, the higher the similarity. Cosine similarity is applicable to high-dimensional feature vectors and is insensitive to the scale of the feature. It calculates the cosine value of the angle between two feature vectors. The closer the value is to 1, the higher the similarity.

[0039] In this embodiment, after calculating the similarity between the first feature information and the second feature information, the similarity is normalized to obtain target data; the target data is mapped to a target interval; if the target data is greater than a matching threshold, it is considered that the second audio signal matches the reference audio signal, and the matching threshold is a value within the target interval.

[0040] In this embodiment, the similarity can be normalized and mapped to a target interval, such as [0, 1]. Normalization can be performed using methods such as linear transformation and logarithmic transformation, and the normalized similarity value (target data) is used as the matching degree. The higher the matching degree, the more similar the second audio signal is to the reference audio signal, and the greater the possibility of the corresponding audio scene. A matching degree threshold can be set. If the matching degree exceeds the threshold, it is considered that the second audio signal matches the reference audio signal and the corresponding audio scene is determined; if the matching degree is lower than the threshold, it can be analyzed or compared with other reference audio signals.

[0041] For example, suppose the cosine similarity between the first feature information of the second audio signal and the second feature information of a reference audio signal is calculated to be 0.8. After normalization, it is used as the matching degree. If the matching degree threshold is set to 0.7, since 0.8 is greater than 0.7, it can be considered that the second audio signal matches the reference audio signal, thereby determining the corresponding audio scene.

[0042] It can be concluded from the above that this embodiment ensures the effective capture and quantification of subtle differences between audio signals by calculating the similarity between the second audio signal and the reference audio signal at the feature level, providing more accurate data support for subsequent audio scene recognition. Through comparative analysis of feature information, it is possible to more accurately determine which reference audio signal the second audio signal is closest to, thereby quickly locking the corresponding audio scene. This not only reduces the possibility of misjudgment, but also improves the speed and stability of recognition.

[0043] In one embodiment of the present disclosure, it also includes: The bit rate at which the second audio signal is transmitted is adjusted based on the sensitivity of the second audio signal to the bit rate.

[0044] In this embodiment, the bit rate determines the bandwidth and transmission quality occupied by the audio signal during transmission. The first characteristic information reflects various characteristics of the second audio signal, and the sensitivity of the audio signal to bit rate changes can be determined by analyzing the characteristics of the first characteristic information.

[0045] In one embodiment of the present disclosure, adjusting the bit rate of the second audio signal transmission based on the sensitivity of the second audio signal to the bit rate includes: determining, according to the first characteristic information, a sensitivity of the second audio signal to a bit rate; The bit rate at which the second audio signal is transmitted is adjusted based on the sensitivity of the second audio signal to the bit rate.

[0046] In this embodiment, the first feature information may include spectrum features, time domain features, etc.

[0047] For example, spectral features can reveal the frequency distribution of audio signals. If the audio signal contains abundant high-frequency components, it indicates that it is more sensitive to bit rate changes, because high bit rates can better preserve high-frequency details. Time domain features can reflect the change of audio signals over time. If the signal changes dramatically, it indicates that a higher bit rate is required for accurate transmission.

[0048] In this embodiment, the sensitivity of the second audio signal to the bit rate may be determined by a machine learning algorithm.

[0049] For example, a neural network model is established, the first feature information is input, and the sensitivity value to the bit rate is output.

[0050] Exemplarily, if the second audio signal is highly sensitive to bit rate, it means that a smaller bit rate change will have a greater impact on the audio quality. In this case, the bit rate of the second audio signal during transmission can be increased to ensure the audio quality. For example, if it is a high-pitched part in music or a clearly pronounced part in speech, a higher bit rate is required for accurate transmission. If the sensitivity is low, it means that the audio signal is not very sensitive to bit rate changes. The bit rate can be appropriately reduced to save bandwidth resources. For example, for some background sounds or relatively stable audio parts, the bit rate of the second audio signal during transmission can be reduced without significantly affecting the audio quality.

[0051] It can be concluded from the above that this embodiment fully considers the characteristics of the audio signal itself, avoiding the waste of resources or insufficient transmission quality caused by blindly setting a fixed bit rate. Fine-tuning is performed according to the sensitivity of the audio signal to bit rate changes, which not only ensures the clear transmission of key audio information, but also effectively saves bandwidth resources. The flexibility and efficiency of audio transmission are improved, ensuring the best listening experience in different network environments.

[0052] In one embodiment of the present disclosure, adjusting the bit rate of the second audio signal transmission based on the sensitivity of the second audio signal to the bit rate includes: In response to the sensitivity of the second audio signal to the bit rate being greater than the first value, transmitting the second audio signal based on the first bit rate; In response to the sensitivity of the second audio signal to the bit rate being greater than a second value and less than or equal to the first value, transmitting the second audio signal based on a second bit rate; In response to the sensitivity of the second audio signal to the bit rate being less than a second value, transmitting the second audio signal based on a third bit rate; The first value is greater than the second value, the first bit rate is greater than the second bit rate, and the second bit rate is greater than the third bit rate.

[0053] In this embodiment, the first value and the second value are used to divide the threshold of the bit rate sensitivity interval of the second audio signal. The first value is greater than the second value, which means that the first value represents a higher sensitivity level and the second value represents a relatively lower sensitivity level.

[0054] In this embodiment, when the sensitivity of the second audio signal to the bit rate is greater than the first value, it indicates that the second audio signal is very sensitive to the change of the bit rate. In this case, the first bit rate is adopted for transmission. Highly sensitive audio signals require a higher bit rate to accurately transmit their details and quality, so as to avoid serious degradation of audio quality due to insufficient bit rate. For example, for the complex instrument performance part in high-quality music audio or the important information part in high-definition voice audio, if these parts are transmitted using a low bit rate, many key details may be lost, affecting the listening effect.

[0055] When the sensitivity of the second audio signal is in this interval, it indicates that it is sensitive to the bit rate to a certain extent, but not as strongly as the signal in the high sensitivity interval. At this time, the second bit rate is used for transmission. The second bit rate is lower than the first bit rate because the audio signal in this interval does not require a high bit rate like the high sensitivity signal to ensure quality, but requires a higher bit rate than the low sensitivity signal. For example, some ordinary music melody parts or relatively stable voice communication parts, these parts need to ensure audio quality to a certain extent, but some compromises can be made in the bit rate to balance transmission efficiency and quality.

[0056] When the sensitivity of the second audio signal to the bit rate is less than the second value, it indicates that the second audio signal is not very sensitive to the change of the bit rate. In this case, a lower third bit rate can be used for transmission.

[0057] For low-sensitivity audio signals, even if a lower bit rate is used for transmission, it will not have a significant impact on the audio quality. For example, some background noise, simple environmental sound effects, etc. These audio signals do not require high quality. Using a low bit rate can save bandwidth resources and improve transmission efficiency.

[0058] It can be concluded from the above that when the audio signal in this embodiment is highly sensitive to the bit rate, a higher first bit rate is used to ensure that the sound quality is not damaged; when the sensitivity is moderate or low, the bit rate is gradually reduced to save network resources. This effectively balances the audio quality and transmission cost, making audio transmission more flexible and efficient. In addition, the multi-level bit rate strategy also improves the user experience and ensures that stable and smooth audio quality can be obtained in different network environments.

[0059] In one embodiment of the present disclosure, it also includes: The bit rate of the second audio signal transmission is adjusted based on the network bandwidth.

[0060] In this embodiment, the network bandwidth refers to the amount of data that can be transmitted by the network within a specific time. A higher network bandwidth means that more data can be transmitted, thereby supporting higher quality audio signal transmission.

[0061] During audio transmission, the bit rate can be adjusted in real time according to changes in network bandwidth. If the network bandwidth decreases, the bit rate can be reduced to prevent audio freezes or interruptions; if the network bandwidth increases, the bit rate can be increased to improve audio quality.

[0062] In one embodiment of the present disclosure, adjusting the bit rate of the second audio signal transmission based on the network bandwidth includes: In response to the network bandwidth being greater than the first bit number, transmitting the second audio signal based on a fourth bit rate; In response to the network bandwidth being less than the first bit number, determining a bit rate for transmitting the second audio signal based on the importance of the first feature information; The first feature information is feature information of the second audio signal.

[0063] In this embodiment, the fourth bit rate represents a specific data transmission rate, with bits per second (bps) as a unit. When the network bandwidth is greater than the first bit number, the fourth bit rate is selected to transmit the second audio signal.

[0064] In this embodiment, the fourth bit rate may be determined according to actual application requirements and experience, and factors considered in determining the fourth bit rate may include the type of audio (such as music, voice, etc.), the needs of the target audience (such as high-fidelity music lovers may need a higher bit rate), network stability, etc. For example, for high-quality music transmission, the fourth bit rate may be set to 320 kbps; while for general voice calls, the fourth bit rate may be relatively low, such as 128 kbps.

[0065] In this embodiment, when the monitored network bandwidth is greater than the first bit rate, it indicates that the current network condition is relatively good and there is sufficient bandwidth to support high-quality audio transmission. At this time, the second audio signal can be transmitted based on the fourth bit rate.

[0066] For example, if the first bit rate is set to 1 Mbps, when the network bandwidth is greater than this value, a bit rate of 320 kbps can be selected to transmit the audio signal to ensure high fidelity and rich details of the audio.

[0067] When the network bandwidth is less than the first bit number, it indicates that network resources are relatively tight and the bit rate of audio transmission needs to be selected more carefully to avoid network congestion and degradation of audio transmission quality. At this time, the bit rate of the second audio signal transmission can be determined based on the importance of the first feature information. The first feature information is the feature information of the second audio signal, which may include spectrum features, time domain features, etc. These features may reflect different characteristics and importance of the audio signal.

[0068] In this embodiment, the importance of the first feature information is determined based on the spectrum features and time domain features of the first feature information.

[0069] In this embodiment, the second audio signal can be converted from the time domain to the frequency domain by fast Fourier transform or other methods to analyze the energy distribution of different frequency components. The part with energy exceeding the preset area is determined as an important part, such as the main melody instrument in music or the vowel part in speech.

[0070] Analyze the changes of audio signals over time. The transient parts in audio, such as the percussion sound of percussion instruments or the plosive sound in speech, often have obvious mutations in the time domain, and the characteristic information of these transient parts is the important part.

[0071] In this embodiment, the importance is divided into high priority, medium priority and low priority.

[0072] In the case of limited network bandwidth, a higher bit rate is allocated to the high priority part first. For example, if the network bandwidth can only support a total bit rate of Xbps, and the audio signal is divided into three priority parts: high, medium, and low, the bit rate can be allocated according to a certain ratio (such as 50% for the high priority part, 30% for the medium priority part, and 20% for the low priority part).

[0073] During audio transmission, as the network bandwidth changes and the audio signal changes dynamically, the bit rate determined based on the importance of the first feature information can be adjusted in real time. If the network bandwidth improves, the bit rate of the important part can be appropriately increased to improve the audio quality; if the network bandwidth further deteriorates, the bit rate of the low priority part can be further reduced.

[0074] It can be concluded from the above that this embodiment not only effectively avoids audio freezes or interruptions that may occur when the network is congested, but also ensures the continuity of the user experience by monitoring the network bandwidth status in real time and adjusting the bit rate accordingly; at the same time, when the network bandwidth is sufficient, it can automatically increase the bit rate to provide users with higher quality audio enjoyment, and enhance the adaptability and satisfaction of audio transmission. In addition, this embodiment also takes into account the importance of the first feature information, and adjusts the bit rate under the premise of ensuring that the transmission of key audio features is not affected, further ensuring the integrity and accuracy of audio transmission, and bringing users a smoother and higher-quality audio experience.

[0075] Corresponding to the audio transmission processing method of the above embodiment, Figure 2 This is a structural block diagram of an audio transmission processing device provided by an embodiment of the present disclosure. For ease of explanation, only the parts related to the embodiment of the present disclosure are shown. Figure 2 The audio transmission processing device 20 includes: a pre-processing module 21, a scene determination module 22, and a signal transmission module 23.

[0076] The preprocessing module 21 is used to preprocess the first audio signal to obtain a second audio signal; A scene determination module 22, configured to determine an audio scene corresponding to the second audio signal based on a matching degree between the second audio signal and the reference audio signal; The signal transmission module 23 is configured to select a target channel based on the audio scene to transmit the second audio signal.

[0077] In one embodiment of the present disclosure, the audio transmission processing device 20 further includes: a matching degree determination module; the matching degree determination module is specifically used to: Calculating the similarity between the first feature information and the second feature information; Determining a matching degree between the second audio signal and the reference audio signal based on a similarity between the first feature information and the second feature information; The first feature information is feature information of the second audio signal, and the second feature information is feature information of the reference audio signal.

[0078] In an embodiment of the present disclosure, the audio transmission processing device 20 further includes: a first bit rate adjustment module; the first bit rate adjustment module is specifically used to: The bit rate at which the second audio signal is transmitted is adjusted based on the sensitivity of the second audio signal to the bit rate.

[0079] In one embodiment of the present disclosure, the first bit rate adjustment module is further configured to: determining, according to the first characteristic information, a sensitivity of the second audio signal to a bit rate; The bit rate at which the second audio signal is transmitted is adjusted based on the sensitivity of the second audio signal to the bit rate.

[0080] In one embodiment of the present disclosure, the first bit rate adjustment module is further configured to: In response to the sensitivity of the second audio signal to the bit rate being greater than the first value, transmitting the second audio signal based on the first bit rate; In response to the sensitivity of the second audio signal to the bit rate being greater than a second value and less than or equal to the first value, transmitting the second audio signal based on a second bit rate; In response to the sensitivity of the second audio signal to the bit rate being less than a second value, transmitting the second audio signal based on a third bit rate; The first value is greater than the second value, the first bit rate is greater than the second bit rate, and the second bit rate is greater than the third bit rate.

[0081] In an embodiment of the present disclosure, the audio transmission processing device 20 further includes: a second bit rate adjustment module; the second bit rate adjustment module is specifically used to: The bit rate of the second audio signal transmission is adjusted based on the network bandwidth.

[0082] In one embodiment of the present disclosure, the second bit rate adjustment module is further configured to: In response to the network bandwidth being greater than the first bit number, transmitting the second audio signal based on a fourth bit rate; In response to the network bandwidth being less than the first bit number, determining a bit rate for transmitting the second audio signal based on the importance of the first feature information; The first feature information is feature information of the second audio signal.

[0083] See also Figure 3 , Figure 3 Schematic block diagram of an electronic device provided by an embodiment of the present disclosure. Figure 3 The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303 and one or more memories 304. The processors 301, input devices 302, output devices 303 and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of the modules in the above-mentioned device embodiments, such as Figure 2 The functions of modules 21 to 23 are shown.

[0084] It should be understood that in the embodiment of the present disclosure, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0085] The input device 302 may include a touch panel, a fingerprint collection sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.

[0086] The memory 304 may include a read-only memory and a random access memory, and provide instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0087] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the audio transmission processing method provided in the embodiments of the present disclosure, and can also execute the implementation methods of the electronic device described in the embodiments of the present disclosure, which will not be repeated here.

[0088] In another embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by the processor, all or part of the processes in the above-mentioned embodiment method are implemented, and the computer program can also be completed by instructing the relevant hardware through the computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0089] The computer-readable storage medium may be an internal storage unit of the electronic device of any of the aforementioned embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0090] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0091] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the electronic devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0092] In the several embodiments provided in the present application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present disclosure.

[0094] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. An audio transmission processing method, characterized in that: include: Preprocessing the first audio signal to obtain a second audio signal; determining an audio scene corresponding to the second audio signal based on a matching degree between the second audio signal and a reference audio signal; A target channel is selected based on the audio scene to transmit the second audio signal.

2. The audio transmission processing method according to claim 1, characterized in that: Before determining the audio scene corresponding to the second audio signal based on the matching degree between the second audio signal and the reference audio signal, the method further includes: Calculating the similarity between the first feature information and the second feature information; determining a matching degree between the second audio signal and a reference audio signal based on a similarity between the first feature information and the second feature information; The first feature information is feature information of the second audio signal, and the second feature information is feature information of the reference audio signal.

3. The audio transmission processing method according to claim 2, characterized in that: Also includes: The bit rate at which the second audio signal is transmitted is adjusted based on the sensitivity of the second audio signal to the bit rate.

4. The audio transmission processing method according to claim 3, characterized in that: The adjusting the bit rate of the second audio signal transmission based on the sensitivity of the second audio signal to the bit rate comprises: determining, according to the first characteristic information, a sensitivity of the second audio signal to a bit rate; The bit rate at which the second audio signal is transmitted is adjusted based on the sensitivity of the second audio signal to the bit rate.

5. The audio transmission processing method according to claim 3, characterized in that: The adjusting the bit rate of the second audio signal transmission based on the sensitivity of the second audio signal to the bit rate comprises: In response to the sensitivity of the second audio signal to the bit rate being greater than the first value, transmitting the second audio signal based on the first bit rate; In response to the sensitivity of the second audio signal to the bit rate being greater than a second value and less than or equal to the first value, transmitting the second audio signal based on a second bit rate; In response to the sensitivity of the second audio signal to the bit rate being less than a second value, transmitting the second audio signal based on a third bit rate; The first value is greater than the second value, the first bit rate is greater than the second bit rate, and the second bit rate is greater than the third bit rate.

6. The audio transmission processing method according to claim 1, characterized in that: Also includes: The bit rate of the second audio signal transmission is adjusted based on the network bandwidth.

7. The audio transmission processing method according to claim 6, characterized in that: The adjusting the bit rate of the second audio signal transmission based on the network bandwidth includes: In response to the network bandwidth being greater than the first bit number, transmitting the second audio signal based on a fourth bit rate; In response to the network bandwidth being less than the first bit number, determining a bit rate for transmitting the second audio signal based on the importance of the first feature information; The first feature information is feature information of the second audio signal.

8. An audio transmission processing device, characterized in that: include: A preprocessing module, used for preprocessing the first audio signal to obtain a second audio signal; a scene determination module, configured to determine an audio scene corresponding to the second audio signal based on a matching degree between the second audio signal and a reference audio signal; A signal transmission module is used to select a target channel based on the audio scene to transmit the second audio signal.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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